Systems and methods to determine a risk factor related to dehydration and thermal stress of a subject

ABSTRACT

Systems and methods to determine a risk factor related to dehydration and thermal stress of a subject are disclosed. Exemplary implementations may: generate output signals, by one or more sensors worn on a body of a subject, conveying information related to one or more of location of the subject, motion of the subject, temperature of the subject, cardiovascular parameters of the subject; store information related to the subject; obtain the output signals; determine in an ongoing manner, from the output signals, values of a water loss metric that correlates with estimated percentage of bodyweight of the subject lost in water; obtain heat index information for a contextual environment surrounding the subject; determine in an ongoing manner, from the output signals, values of an exertion metric that correlates with exertion of the subject due to work; and determine in an ongoing manner values for an aggregated risk factor of the subject.

FIELD OF THE DISCLOSURE

The present disclosure relates to systems and methods to determine arisk factor related to dehydration and thermal stress of a subject.

BACKGROUND

By the time a worker is aware of their dehydration and/or feels hot, theworker's body has likely lost 2% of their body weight in water. At thistime, replenishment of the lost water cannot occur quick enough toeffectively cool the body. Dehydration and thermal stress of a body of asubject may affect cognitive function and consequently contribute toinjury, poor decisions, lack of perception, and/or other negativeeffects.

SUMMARY

One aspect of the present disclosure relates to a system configured topredict dehydration and thermal stress of a subject. The subject maywear a plurality of sensors on their body by which data is collectedabout the subject. The data may include information related to the heartof the subject, oxygen consumption of the subject, motion of thesubject, location of the subject, and/or other data. Based on thelocation of the subject, information related to ambient conditions of anenvironment the subject is in may be obtained. Based on the datacollected, a percentage of bodyweight that the subject lost in water(i.e., sweat) may be determined. Further based on the data, work done bythe subject may be determined. Based on the percentage of bodyweightlost in water, the work done, and the ambient conditions, an overallrisk value may be determined that is indicative of how susceptible thesubject is to thermal stress and dehydration at that moment. Such riskvalue may allow the subject to prevent future thermal stress anddehydration and thus avoid increasing their core body temperature,overexertion, and/or other negative effects.

One aspect of the present disclosure relates to a system configured todetermine a risk factor related to dehydration and thermal stress of asubject. The system may include one or more hardware processorsconfigured by machine-readable instructions, a sensor group of one ormore sensors worn on a body of a subject, and an electronic storage. Theelectronic storage may be configured to store information related to thesubject, the information conveyed by the output signals, and/or otherinformation.

The machine-readable instructions may be configured by instructioncomponents. The instruction components may include computer programcomponents. The instruction components may include one or more of signalobtaining component, water loss component, ambient condition component,exertion component, oxygen determination component, work determinationcomponent, risk determination component, and/or other instructioncomponents.

The sensor group of the one or more sensors may be configured togenerate output signals. The output signals may convey informationrelated to one or more of location of the subject, motion of thesubject, temperature of the subject, cardiovascular parameters of thesubject, and/or other information.

The signal obtaining component may be configured to obtain the outputsignals. The output signals may be analog signals, digital signals,and/or encodings.

The water loss component may be configured to determine in an ongoingmanner, from the output signals, values of a water loss metric thatcorrelates with estimated percentage of bodyweight of the subject lostin water.

The ambient condition component may be configured to obtain heat indexinformation for a contextual environment surrounding the subject.

The exertion component may be configured to determine in an ongoingmanner, from the output signals, values of an exertion metric thatcorrelates with exertion of the subject due to work.

The risk determination component may be configured to determine in anongoing manner values for an aggregated risk factor of the subject. Thevalues of the aggregated risk factor may be determined by aggregatingvalues of the water loss metric, the heat index information, and theexertion metric for the subject.

As used herein, the term “obtain” (and derivatives thereof) may includeactive and/or passive retrieval, determination, derivation, transfer,upload, download, submission, and/or exchange of information, and/or anycombination thereof. As used herein, the term “effectuate” (andderivatives thereof) may include active and/or passive causation of anyeffect, both local and remote. As used herein, the term “determine” (andderivatives thereof) may include measure, calculate, compute, estimate,approximate, generate, and/or otherwise derive, and/or any combinationthereof.

These and other features, and characteristics of the present technology,as well as the methods of operation and functions of the relatedelements of structure and the combination of parts and economies ofmanufacture, will become more apparent upon consideration of thefollowing description and the appended claims with reference to theaccompanying drawings, all of which form a part of this specification,wherein like reference numerals designate corresponding parts in thevarious figures. It is to be expressly understood, however, that thedrawings are for the purpose of illustration and description only andare not intended as a definition of the limits of the invention. As usedin the specification and in the claims, the singular form of ‘a’, ‘an’,and ‘the’ include plural referents unless the context clearly dictatesotherwise.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a system configured to determine a risk factorrelated to dehydration and thermal stress of a subject, in accordancewith one or more implementations.

FIG. 2 illustrates a method to determine a risk factor related todehydration and thermal stress of a subject, in accordance with one ormore implementations.

FIG. 3 illustrates an example implementation of a system configured todetermine a risk factor related to dehydration and thermal stress of asubject, in accordance with one or more implementations.

DETAILED DESCRIPTION

FIG. 1 illustrates a system 100 configured to determine a risk factorrelated to dehydration and thermal stress of a subject, in accordancewith one or more implementations. In some implementations, system 100may include one or more servers 102. Server(s) 102 may be configured tocommunicate with one or more client computing platforms 104 and one ormore sensor groups 108 according to a client/server architecture and/orother architectures. Client computing platform(s) 104 may be configuredto communicate with other client computing platforms via server(s) 102and/or according to a peer-to-peer architecture and/or otherarchitectures. Users may access system 100 via client computingplatform(s) 104.

Server(s) 102 may be configured by machine-readable instructions 106.Machine-readable instructions 106 may include one or more instructioncomponents. The instruction components may include computer programcomponents. The instruction components may include one or more of signalobtaining component 112, water loss component 114, ambient conditioncomponent 116, exertion component 118, oxygen determination component120, work determination component 122, risk determination component 124,and/or other instruction components.

Sensor group 108 may include one or more sensors worn on a body of asubject. The one or more sensors may be configured to generate outputsignals conveying information related to one or more of location of thesubject, motion of the subject, temperature of the subject,cardiovascular parameters of the subject, and/or other information. Theone or more sensors may include one or more of an orientation sensor, alocation sensor, a pressure sensor, a temperature sensor, a lightsensor, an audio sensor, cardiovascular sensor, and/or other sensors.

In some implementations, a location sensor may be configured to generateoutput signals conveying information related to the location of thesubject and/or other information. The information related to thelocation derived from output signals of a location sensor may define oneor more of a geo-location of the subject, an elevation of the subject,and/or other measurements. A location sensor may include one or more ofa GPS, an altimeter, and/or other devices. The location of the subjectmay be a location of a contextual environment of the subject. Thecontextual environment may be the immediate space surrounding thesubject and of which the subject is operating and/or working in. Theimmediate area may be a particular radius surrounding the subjectdefined by the location sensor, an operator user, the subject, and/or byother definition. The contextual environment may change over time uponobtainment of an assigned route and/or a predicted route of the subject.

The information related to the motion of the subject may includeacceleration, orientation, speed of motion, joint angles, and/or otherinformation related to the motion of the subject. An orientation sensormay be configured to generate output signals conveying orientationinformation and/or other information. Orientation information derivedfrom output signals of an orientation sensor may define an orientationof the subject. In some implementations, orientation may refer to one ormore of a pitch angle, a roll angle, a yaw angle, heading, pointingdirection, and/or other measurements. An orientation sensor may includean inertial measurement unit (IMU) such as one or more of anaccelerometer, a gyroscope, a magnetometer, Inclinometers, Electronicnose, Infrared Imagers, Micro-bolometers, micro-displays (DMD), Digitalmicro-mirror device, Optical Switches, and/or other devices.

A pressure sensor may be configured to generate output signals conveyingpressure information and/or other information. Pressure informationderived from output signals of a pressure sensor may define a force perunit area imparted to the pressure sensor. A pressure sensor may includeone or more of a piezoresistive strain gauge, a capacitive pressuresensor, an electromagnetic pressure sensor, a piezoelectric sensor, astrain-gauge, and/or other pressure sensors.

A temperature sensor may be configured to generate output signalsconveying information related to the temperature of the subject and/orother information. The information related to the temperature of thesubject derived from output signals of a temperature sensor may defineone or more of a temperature at the temperature sensor, temperaturewithin a threshold range of the temperature sensor, biometricinformation, and/or other measure of temperature of the subject. Thebiometric information may include one or more of skin temperaturereadings, internal body temperature readings, and/or other readings. Insome implementations, the information related to the temperature of thesubject may define one or more of a temperature at the temperaturesensor, temperature within a threshold range of the temperature sensor,and/or other measure of temperature of a contextual environment of thesubject. A temperature sensor may include one or more of a thermocouple,a resistive temperature Measuring device, an infrared sensor, abimetallic device, a thermometer, and/or other temperature sensors.

A light sensor may be configured to generate output signals conveyingambient light information and/or other information. The ambient lightinformation derived from output signals of a light sensor may defineintensity and/or presence (or absence) of light or other electromagneticradiation incident on the light sensor. A light sensor may include oneor more of a photodiode, an active-pixel sensor, photovoltaic, and/orother sensors.

An audio input sensor may be configured to receive audio input. An audioinput sensor may include a sound transducer and/or other sensorconfigured to convert sound (e.g., air pressure variation) into anelectrical signal. By way of non-limiting illustration, an audio inputsensor may include a microphone.

One or more cardiovascular sensors may be configured to generate outputsignals conveying biometric information related to heart, lungs, andcirculation of the subject. The biometric information may include valuesfor the cardiovascular parameters of the subject, and/or other valuesfor other biometric parameters. The cardiovascular parameters mayinclude heart rate, a resting heart rate of the subject, a respiratoryrate of the subject, blood pressure of the subject, oxygen saturation ofthe subject, heart variability, heartbeat strength, heartbeat rhythm,and/or other cardiovascular parameters. The one or more cardiovascularsensors may include one or more an electrodermal activity (EDA), anelectrocardiography (EKG or ECG) sensor, a blood volume pulse (BVP)sensor, a respiration sensor, a blood pressure sensor, and/or othercardiovascular sensors. Other sensors that may convey the biometricinformation may include one or more of an electrodermal activity (EDA),an electromyography (EMG) sensor, and/or other sensors.

Electronic storage 132 may be configured to store information related tothe subject, the information related to one or more of the location ofthe subject, the motion of the subject, the temperature of the subject,the cardiovascular parameters of the subject, other information conveyedby the output signals, and/or other information. The information relatedto the subject may include values that define subject parameters. Thesubject parameters may include gender, weight, height, age, race,underlying conditions, and/or other subject parameters.

Signal obtaining component 112 may be configured to obtain the outputsignals. The output signals may be analog signals, digital signals,encoded signals, combinations thereof, and/or other signals.

Ambient condition component 116 may be configured to obtain conditioninformation related to the ambient conditions of the contextualenvironment surrounding the subject. The condition information mayinclude values for condition parameters. The condition parameters mayinclude one or more of a temperature, humidity, precipitation, anultraviolet index, visibility, pressure, dew point, wind direction, windgust, cloud coverage, and/or other condition parameters. Determining thevalues of the water loss metric may be based on work done by the subjectand the condition information. In some implementations, the conditioninformation may be stored to electronic storage 132. In someimplementations, the condition information may be stored to electronicstorage 132 and associated with a particular date and/or time.

Oxygen determination component 120 may be configured to determinecurrent oxygen consumption of the subject. Such determination may be inan ongoing manner. Such determination may be from the output signals.Determining the current oxygen consumption may be based on informationrelated to the motion of the subject, the ambient conditions of thecontextual environment, the information related to the subject, thevalues of the cardiovascular parameters, and/or other information. Theoutput signals used to determine the current oxygen consumption mayconvey information related to a volume of oxygen currently consumed bythe subject at the particular moment in time. The current oxygenconsumption may be stored to electronic storage 132 upon determination.In some implementations, the current oxygen consumption may be storedand associated with a corresponding date and/or time.

Oxygen determination component 120 may be configured to determinemaximal oxygen consumption. The maximal oxygen consumption maycharacterize a maximum volume of oxygen the subject has ever consumed.Determining the maximal oxygen consumption may be from the outputsignals. In some implementations, determining the maximal oxygenconsumption may be based on the information related to the subject(e.g., age, height, weight), the information related to the motion ofthe subject (e.g., speed of the motion), the condition information(e.g., a temperature value, and a humidity value) and/or otherinformation. Determining the maximal oxygen consumption may includedetermining that a particular current oxygen consumption is the maximaloxygen consumption by comparing the particular oxygen consumption withone or more of the current oxygen consumption stored in electronicstorage 132 and defining the maximal oxygen consumption based on thecomparison(s). The maximal oxygen consumption may be stored toelectronic storage 132 upon determination. In some implementations, themaximal oxygen consumption may be stored and associated with acorresponding date and/or time.

Work determination component 122 may be configured to determine workexerted by the subject. The work exerted may be the product of force anddisplacement of an object. Determining the work exerted by the subjectmay be based on the information related to the motion of the subject,the values the cardiovascular parameters of the subject, the currentoxygen consumption, weight of the object, displacement (e.g., heightdisplacement) of the object, repetition of the motion of the subject,and/or other information. The weight of the object and the displacementof the object may be input prior to exertion of the work by the subject.For example, the subject may be instructed to move 100 35-poundcinderblocks. The weight of 35 pounds may be input and a repetition of100 may be entered to determine the work exerted by the subject.Furthermore, the displacement of the object may be entered, such as 200feet. The work exerted by the subject may be stored to electronicstorage 132 upon determination. In some implementations, the workexerted by the subject may be stored and associated with a correspondingdate and/or time.

Water loss component 114 may be configured to determine values of awater loss metric that correlate with estimated percentage of bodyweightof the subject lost in water. Determining the values of the water lossmetric may be in an ongoing manner. The term “ongoing manner” as usedherein may refer to continuing to perform an action (e.g., determine)periodically (e.g., every 30 seconds, every minute, every hour, etc.)until receipt of an indication to terminate. The indication to terminatemay include powering off client computing platform 104, charging one ormore of a battery of client computing platform 104, resetting clientcomputing platform 104, and/or other indications of termination. As usedherein, the term “correlate” (and derivatives thereof) may includeestimate, quantify, correspond to, combinations thereof, and/or otherterms that refer to a relationship in which one value indicates anothervalue. Determining the values of the water loss metric may be from theoutput signals. The water loss metric may be a system of measurement ofhow much water (e.g., sweat) the subject has lost. Determining thevalues of the water loss metric may be based on the work done by thesubject, the condition information, and/or other information.Determining the values of the water loss metric may include forecastmodeling, time series modeling, average risk prediction modeling,weighted average modeling, machine learning, combinations thereof,and/or other determination techniques. The values of the water lossmetric may indicate the estimated percentage, or otherwise estimatedamount, of bodyweight loss of the subject. The values of the water lossmetric may be stored to electronic storage 132. In some implementations,the values of the water loss metric may be stored to electronic storage132 and associated with a particular date and/or time.

Ambient condition component 116 may be configured to obtain heat indexinformation for a contextual environment surrounding the subject. Theheat index information may include values for a current heat index, afuture heat index, and/or other information. In some implementations, aheat index be a temperature of the contextual environment of thesubject. In some implementations, the heat index may account for airtemperature, relative humidity, the wind gust, and/or one or more of thecondition parameter values to presume a temperature at which thecontextual environment that surrounds the subject feels. As such, thecurrent heat index may represent a current temperature of the contextualenvironment that surrounds the subject. The future heat index mayrepresent a future temperature the contextual environment may reach on aparticular day. The future heat index may represent a future peaktemperature of which may be the highest temperature of the particularday. In some implementations, ambient condition component 116 may beconfigured to determine, or otherwise derive, one or more values for aheat index metric, based on the heat index information. The one or morevalues for the heat index metric may correlate with the current heatindex and the future heat index. In some implementations, the heat indexinformation obtained may include the one or more values for the heatindex metric. The heat index information and the one or more values forthe heat index metric may be stored to electronic storage 132. In someimplementations, the heat index information and the one or more valuesfor the heat index metric may be stored to electronic storage 132 andassociated with a particular date and/or time.

Exertion component 118 may be configured to determine heart rate. Suchdetermination may be in an ongoing manner. Such determination may befrom the output signals. Determining the heart rate may be based oninformation related to the motion of the subject, the ambient conditionsof the contextual environment, the information related to the subject,values of the cardiovascular parameters, and/or other information. Theoutput signals used to determine the heart rate may convey informationrelated to values of the cardiovascular parameters. The values of thecardiovascular parameters may define one or more of a resting heartrate, a respiratory rate, blood pressure, oxygen saturation in blood,and/or other measurements of the heart of the subject. The heart rate ofthe subject may indicate beats per minute, heart rate variability,heartbeat strength, heartbeat rhythm, and/or other information. Theheart rate determined may be a current heart rate at a particular momentin time. The heart rate determined may be stored to electronic storage132. In some implementations, the heart rate determined may be stored toelectronic storage 132 and associated with a particular date and/ortime.

Exertion Component 118 may be configured to determine values of anexertion metric. The values of the exertion metric may correlate withexertion of the subject due to the work. The exertion of the subject maybe the use the energy by the subject due to the work exerted by thesubject. Thus, the exertion metric may be system of measurement of howmuch work (e.g., lifting) the subject has done or exerted. Determiningthe values of the exertion metric may be in an ongoing manner.Determining the values of the exertion metric may from the outputsignals. Determining the values of the exertion metric may be based onthe heart rate, the current oxygen consumption, the work done by thesubject, and/or other information. The values of the exertion metric maybe stored to electronic storage 132. In some implementations, the valuesof the exertion metric may be stored to electronic storage 132 andassociated with a particular date and/or time.

Risk determination component 124 may be configured to determine valuesfor an aggregated risk factor of the subject. Determining the aggregatedrisk factor may be in an ongoing manner. The values of the aggregatedrisk factor may be determined by aggregating values of the water lossmetric, the heat index information, the exertion metric for the subject,and/or other information. The values of the aggregated risk factor mayindicate a risk related to thermal stress and dehydration that thesubject is susceptible to. Dehydration in addition to thermal stress ofthe body of the subject may include an increase in core bodytemperature, an increase in heart rate, an increase in oxygenconsumption, a decrease in work, a decrease in efficiency of the work, aglobal cardiopulmonary and neural muscular chain reaction that maydecrease cardiac output, stroke volume, cognitive function, andmechanical output, and/or other negative effects. The values of theaggregated risk factor may be part of a range of risk. For example, therange of risk may span from 0 to 100. The values for an aggregated riskfactor may be a value be within the range such as 15. The range of riskmay include one or more thresholds. The one or more threshold mayindicate different levels of risk such as no risk, moderate risk, anddangerous risk. A threshold may be associated with a particular value ofthe aggregated risk factor. For example, for a moderate risk of thermalstress and dehydration, the value of the aggregated risk factor must beat least 20. For example, for a dangerous risk of thermal stress anddehydration, the value of the aggregated risk factor must be at least40. Determining the aggregated risk factor of the subject may includeforecast modeling, time series modeling, average risk predictionmodeling, weighted average modeling, machine learning, combinationsthereof, and/or other determination techniques. The values for theaggregated risk factor may be stored to electronic storage 132. In someimplementations, the values for the aggregated risk factor may be storedto electronic storage 132 and associated with a particular date and/ortime.

Risk determination component 124 may be configured to determine valuesfor a fatigue risk. The values of the fatigue risk may be indicative ofan increase in tiredness, lethargy, exhaustion, and/or other factorsthat the subject is susceptible to. Furthermore, in someimplementations, the values of the fatigue risk may be indicative of adecrease in perception, performance, motivation, and/or other factorsthat the subject is susceptible to. The values of the fatigue risk maybe part of a range of fatigue risk. For example, the range of fatiguerisk may span from 0 to 100. The values for the fatigue risk may a valuebe within the range such as 35. The range of fatigue risk may includeone or more thresholds. The one or more threshold may indicate differentlevels of risk such as no risk, moderate risk, and dangerous risk. Athreshold may be associated with a particular value of the fatigue risk.Determining the values for the fatigue risk may be in an ongoing manner.Determining the values for the fatigue risk may include dividing thecurrent oxygen consumption by the maximal oxygen consumption. A value ofthe fatigue risk may correlate to recovery time of the subject. Therecovery time may be the length of time required for the body of thesubject (e.g., muscles, tissues, etc.) to repair, rebuild, and/orstrengthen. As such, the higher or more dangerous the values of thefatigue risk, the longer recovery time of the subject may be. The valuesfor the fatigue risk may be stored to electronic storage 132. In someimplementations, the values for the fatigue risk may be stored toelectronic storage 132 and associated with a particular date and/ortime.

FIG. 3 may illustrate an example implementation of a system configuredto determine a risk factor related to dehydration and thermal stress ofa subject, in accordance with one or more implementations. FIG. 3 mayinclude subject 308 whom of which is moving bricks 306 in environment300. By way of non-limiting example, subject 308 may be a solider, amaintenance worker, or otherwise a subject that may exert a copiousamount of energy. Subject 308 may be wearing on their body a Smartwatch302, sensor 304 a, and sensor 304 b. Sensor 304 a may be located nearthe heart of subject 300. Sensor 304 b may be located around the chestof subject 308. Contemporaneous to and due to subject 308 moving bricks306, a value of a water loss metric that correlates with a percentage inbodyweight lost in water by subject 308 may be determined. Furthermore,the heat index information may be obtained for environment 300. The heatindex information may include a value of the heat index metric thatindicates a temperature of 90 degrees Fahrenheit in environment 300.Contemporaneous to and due to subject 308 moving bricks 306, a value forthe exertion metric may be determined that correlates with exertion bysubject 308 due to work. Based on the value of the water loss metric,the heat index information, and the value of the exertion metric, avalue for the aggregated risk factor may be determined that indicateshow susceptible subject 308 is the thermal stress and/or dehydration.The value for the aggregated risk factor may, for example, be presentedon Smartwatch 302.

In some implementations, server(s) 102, client computing platform(s)104, and/or external resources 130 may be operatively linked via one ormore electronic communication links. For example, such electroniccommunication links may be established, at least in part, via a networksuch as the Internet and/or other networks. It will be appreciated thatthis is not intended to be limiting, and that the scope of thisdisclosure includes implementations in which server(s) 102, clientcomputing platform(s) 104, and/or external resources 130 may beoperatively linked via some other communication media.

A given client computing platform 104 may include one or more processorsconfigured to execute computer program components. The computer programcomponents may be configured to enable an expert or user associated withthe given client computing platform 104 to interface with system 100and/or external resources 130, and/or provide other functionalityattributed herein to client computing platform(s) 104. By way ofnon-limiting example, the given client computing platform 104 mayinclude one or more of a desktop computer, a laptop computer, a handheldcomputer, a tablet computing platform, a NetBook, a Smartphone, aSmartwatch, a gaming console, and/or other computing platforms.

For example, in some implementations, the subject may wear a firstclient computing platform that is a Smartwatch. A first sensor group mayinclude one or more of the sensors worn on one or more parts of the bodyof the subject. One or more of the sensors included in the first sensorgroup may be worn on a wrist, a wrist via the first client computingplatform, upper chest, lower chest, upper arm, around the neck, abdomen,and/or other parts of the body of the subject.

External resources 130 may include sources of information outside ofsystem 100, external entities participating with system 100, and/orother resources. In some implementations, some or all of thefunctionality attributed herein to external resources 130 may beprovided by resources included in system 100.

Server(s) 102 may include electronic storage 132, one or more processors134, and/or other components. Server(s) 102 may include communicationlines, or ports to enable the exchange of information with a networkand/or other computing platforms. Illustration of server(s) 102 in FIG.1 is not intended to be limiting. Server(s) 102 may include a pluralityof hardware, software, and/or firmware components operating together toprovide the functionality attributed herein to server(s) 102. Forexample, server(s) 102 may be implemented by a cloud of computingplatforms operating together as server(s) 102.

Electronic storage 132 may comprise non-transitory storage media thatelectronically stores information. The electronic storage media ofelectronic storage 132 may include one or both of system storage that isprovided integrally (i.e., substantially non-removable) with server(s)102 and/or removable storage that is removably connectable to server(s)102 via, for example, a port (e.g., a USB port, a firewire port, etc.)or a drive (e.g., a disk drive, etc.). Electronic storage 132 mayinclude one or more of optically readable storage media (e.g., opticaldisks, etc.), magnetically readable storage media (e.g., magnetic tape,magnetic hard drive, floppy drive, etc.), electrical charge-basedstorage media (e.g., EEPROM, RAM, etc.), solid-state storage media(e.g., flash drive, etc.), and/or other electronically readable storagemedia. Electronic storage 132 may include one or more virtual storageresources (e.g., cloud storage, a virtual private network, and/or othervirtual storage resources). Electronic storage 132 may store softwarealgorithms, information determined by processor(s) 134, informationreceived from server(s) 102, information received from client computingplatform(s) 104, and/or other information that enables server(s) 102 tofunction as described herein.

Processor(s) 134 may be configured to provide information processingcapabilities in server(s) 102. As such, processor(s) 134 may include oneor more of a digital processor, an analog processor, a digital circuitdesigned to process information, an analog circuit designed to processinformation, a state machine, and/or other mechanisms for electronicallyprocessing information. Although processor(s) 134 is shown in FIG. 1 asa single entity, this is for illustrative purposes only. In someimplementations, processor(s) 134 may include a plurality of processingunits. These processing units may be physically located within the samedevice, or processor(s) 134 may represent processing functionality of aplurality of devices operating in coordination. Processor(s) 134 may beconfigured to execute components 112, 114, 116, 118, 120, 122, and/or124, and/or other components. Processor(s) 134 may be configured toexecute components 112, 114, 116, 118, 120, 122, and/or 124, and/orother components by software; hardware; firmware; some combination ofsoftware, hardware, and/or firmware; and/or other mechanisms forconfiguring processing capabilities on processor(s) 134. As used herein,the term “component” may refer to any component or set of componentsthat perform the functionality attributed to the component. This mayinclude one or more physical processors during execution of processorreadable instructions, the processor readable instructions, circuitry,hardware, storage media, or any other components.

It should be appreciated that although components 112, 114, 116, 118,120, 122, and/or 124 are illustrated in FIG. 1 as being implementedwithin a single processing unit, in implementations in whichprocessor(s) 134 includes multiple processing units, one or more ofcomponents 112, 114, 116, 118, 120, 122, and/or 124 may be implementedremotely from the other components. The description of the functionalityprovided by the different components 112, 114, 116, 118, 120, 122,and/or 124 described below is for illustrative purposes, and is notintended to be limiting, as any of components 112, 114, 116, 118, 120,122, and/or 124 may provide more or less functionality than isdescribed. For example, one or more of components 112, 114, 116, 118,120, 122, and/or 124 may be eliminated, and some or all of itsfunctionality may be provided by other ones of components 112, 114, 116,118, 120, 122, and/or 124. As another example, processor(s) 134 may beconfigured to execute one or more additional components that may performsome or all of the functionality attributed below to one of components112, 114, 116, 118, 120, 122, and/or 124.

FIG. 2 illustrates a method 200 to determine a risk factor related todehydration and thermal stress of a subject, in accordance with one ormore implementations. The operations of method 200 presented below areintended to be illustrative. In some implementations, method 200 may beaccomplished with one or more additional operations not described,and/or without one or more of the operations discussed. Additionally,the order in which the operations of method 200 are illustrated in FIG.2 and described below is not intended to be limiting.

In some implementations, method 200 may be implemented in one or moreprocessing devices (e.g., a digital processor, an analog processor, adigital circuit designed to process information, an analog circuitdesigned to process information, a state machine, and/or othermechanisms for electronically processing information). The one or moreprocessing devices may include one or more devices executing some or allof the operations of method 200 in response to instructions storedelectronically on an electronic storage medium. The one or moreprocessing devices may include one or more devices configured throughhardware, firmware, and/or software to be specifically designed forexecution of one or more of the operations of method 200.

An operation 202 may include generating output signals, by a sensorgroup of one or more sensors worn on a body of a subject, conveyinginformation related to one or more of location of the subject, motion ofthe subject, temperature of the subject, cardiovascular parameters ofthe subject. Operation 202 may be performed by one or more hardwareprocessors configured by machine-readable instructions including acomponent that is the same as or similar to sensor group 108, inaccordance with one or more implementations.

An operation 204 may include storing, in electronic storage, informationrelated to the subject. Operation 204 may be performed by one or morehardware processors configured by machine-readable instructionsincluding a component that is the same as or similar to water losscomponent 114, ambient condition component 116, exertion component 118,oxygen determination component 120, work determination component 122,and/or risk determination component 124, and electronic storage 132, inaccordance with one or more implementations.

An operation 206 may include obtaining the output signals. Operation 206may be performed by one or more hardware processors configured bymachine-readable instructions including a component that is the same asor similar to signal obtaining component 112, in accordance with one ormore implementations.

An operation 208 may include determining in an ongoing manner, from theoutput signals, values of a water loss metric that correlates withestimated percentage of bodyweight of the subject lost in water.Operation 208 may be performed by one or more hardware processorsconfigured by machine-readable instructions including a component thatis the same as or similar to water loss component 114, in accordancewith one or more implementations.

An operation 210 may include obtaining heat index information for acontextual environment surrounding the subject. Operation 210 may beperformed by one or more hardware processors configured bymachine-readable instructions including a component that is the same asor similar to ambient condition component 116, in accordance with one ormore implementations.

An operation 212 may include determining in an ongoing manner, from theoutput signals, values of an exertion metric that correlates withexertion of the subject due to work. Operation 212 may be performed byone or more hardware processors configured by machine-readableinstructions including a component that is the same as or similar toexertion component 118, in accordance with one or more implementations.

An operation 214 may include determining in an ongoing manner values foran aggregated risk factor of the subject. The values of the aggregatedrisk factor may be determined by aggregating values of the water lossmetric, the heat index information, and the exertion metric for thesubject. Operation 214 may be performed by one or more hardwareprocessors configured by machine-readable instructions including acomponent that is the same as or similar to risk determination component124, in accordance with one or more implementations.

Although the present technology has been described in detail for thepurpose of illustration based on what is currently considered to be themost practical and preferred implementations, it is to be understoodthat such detail is solely for that purpose and that the technology isnot limited to the disclosed implementations, but, on the contrary, isintended to cover modifications and equivalent arrangements that arewithin the spirit and scope of the appended claims. For example, it isto be understood that the present technology contemplates that, to theextent possible, one or more features of any implementation can becombined with one or more features of any other implementation.

1. A system configured to determine a risk factor related to dehydrationand thermal stress of a subject, the system comprising: a sensor groupof sensors worn on a body of a subject, configured to generate outputsignals conveying information related to one or more of: location of thesubject, motion of the subject, temperature of the subject,cardiovascular parameters of the subject; electronic storage configuredto store the information related to the subject; and one or moreprocessors configured by machine-readable instructions to: obtain theoutput signals; determine in an ongoing manner, from the output signals,values of a water loss metric that quantify an estimated percentage ofbodyweight of the subject lost in water; obtain heat index informationfor a contextual environment surrounding the subject; determine in anongoing manner, from the output signals, values of an exertion metricthat quantifies exertion of the subject due to work, wherein theexertion metric is separate and discrete from the water loss metric; anddetermine, in an ongoing manner, individual values for an aggregatedrisk factor of the subject that indicates risk of thermal stress anddehydration of the subject at a given point in time, wherein the valuesof the aggregated risk factor are determined by aggregating values ofthe water loss metric, the heat index information, and the exertionmetric for the subject.
 2. The system of claim 1, wherein the one ormore processors are further configured to: determine in an ongoingmanner, from the output signals, heart rate and current oxygenconsumption of the subject based on information related to the motion ofthe subject, ambient conditions of the contextual environment, and theinformation related to the subject; and wherein determining the valuesof the exertion metric is based on the heart rate and the current oxygenconsumption.
 3. The system of claim 2, wherein the output signals usedto determine the heart rate convey information related to values of thecardiovascular parameters.
 4. The system of claim 2, wherein the outputsignals used to determine the current oxygen consumption conveyinformation related to a volume of oxygen currently consumed by thesubject.
 5. The system of claim 2, wherein the one or more processorsare further configured to: determine, from the output signals, maximaloxygen consumption; and determine in an ongoing manner values for afatigue risk by dividing the current oxygen consumption by the maximaloxygen consumption, the fatigue risk correlating to recovery time of thesubject.
 6. The system of claim 5, wherein the maximal oxygenconsumption characterizes the maximum volume of oxygen the subject hasconsumed.
 7. The system of claim 2, wherein the one or more processorsare further configured to: determine the work based on informationrelated to the motion of the subject, information related to thecardiovascular parameters of the subject, and the current oxygenconsumption.
 8. The system of claim 7, wherein the one or moreprocessors are further configured to: obtain condition informationrelated to ambient conditions of the contextual environment surroundingthe subject, wherein determining the values of the water loss metric isbased on the work and the condition information.
 9. The system of claim1, wherein the heat index information includes a current heat index anda future heat index, wherein the one or more processors are furtherconfigured to: determine a value for a heat index metric that correlateswith the current heat index and the future heat index.
 10. The system ofclaim 1, wherein determining in an ongoing manner values for theaggregated risk factor of the subject includes forecast modeling, timeseries modeling, average risk prediction modeling, and/or weightedaverage modeling.
 11. A method to determine a risk factor related todehydration and thermal stress of a subject, the method comprising:generating output signals, by a sensor group of sensors worn on a bodyof a subject, conveying information related to one or more of: locationof the subject, motion of the subject, temperature of the subject,cardiovascular parameters of the subject; storing, in electronicstorage, the information related to the subject; obtaining, using one ormore processors, the output signals; determining in an ongoing manner,using the one or more processors, from the output signals, values of awater loss metric that quantify an estimated percentage of bodyweight ofthe subject lost in water; obtaining heat index information, using theone or more processors, for a contextual environment surrounding thesubject; determining in an ongoing manner, using the one or moreprocessors, from the output signals, values of an exertion metric thatquantifies exertion of the subject due to work, wherein the exertionmetric is separate and discrete from the water loss metric; anddetermining in an ongoing manner, using the one or more processors,individual values for an aggregated risk factor of the subject thatindicates risk of thermal stress and dehydration of the subject at agiven point in time, wherein the values of the aggregated risk factorare determined by aggregating values of the water loss metric, the heatindex information, and the exertion metric for the subject.
 12. Themethod of claim 11, further comprising: determine in an ongoing mannerusing the one or more processors, from the output signals, heart rateand current oxygen consumption of the subject based on informationrelated to the motion of the subject, ambient conditions of thecontextual environment, and the information related to the subject; andwherein determining the values of the exertion metric is based on theheart rate and the current oxygen consumption.
 13. The method of claim12, wherein the output signals used to determine the heart rate conveyinformation related to values of the cardiovascular parameters.
 14. Themethod of claim 12, wherein the output signals used to determine thecurrent oxygen consumption convey information related to a volume ofoxygen currently consumed by the subject.
 15. The method of claim 12,further comprising: determining, from the output signals, using the oneor more processors, maximal oxygen consumption; and determining in anongoing manner, using the one or more processors, values for a fatiguerisk by dividing the current oxygen consumption by the maximal oxygenconsumption, the fatigue risk correlating to recovery time of thesubject.
 16. The method of claim 15, wherein the maximal oxygenconsumption characterizes the maximum volume of oxygen the subject hasconsumed.
 17. The method of claim 12, further comprising: determining,using the one or more processors, the work based on information relatedto the motion of the subject, information related to the cardiovascularparameters of the subject, and the current oxygen consumption.
 18. Themethod of claim 17, further comprising: obtaining, using the one or moreprocessors, condition information related to ambient conditions of thecontextual environment surrounding the subject, wherein determining thevalues of the water loss metric is based on the work and the conditioninformation.
 19. The method of claim 11, wherein the heat indexinformation includes a current heat index and a future heat index,further comprising: determining, using the one or more processors, avalue for a heat index metric that correlates with the current heatindex and the future heat index.
 20. The method of claim 11, whereindetermining in an ongoing manner values for the aggregated risk factorof the subject includes forecast modeling, time series modeling, averagerisk prediction modeling, and/or weighted average modeling.